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Training 3 Transcript

 

Shared Flows
0:03
wow all right so I didn't get a chance to do as many
0:08
um analyzes as I wanted to but I didn't have a pretty good start on uh looking at the Airbnb Destiny density of
0:14
California's population centers so this is mostly going to look at the San Francisco area LA and then San Diego
0:20
down here um I've colored the each of these dots represents an actual Airbnb BNB location
0:27
and I've colored them by price so to get a better look at the price and
0:33
each area we can go ahead and go into the next slide and we can see that majority of them are down pretty low but
0:39
there are quite a bit that are pretty high up here so if you look at this one as an example um we can see this is in Beverly Hills
0:46
and it's 25 000 a night for that location so um that's quite a bit but um
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but yeah if I just kind of Click around here you can kind of see that you know there's a bunch of different options and varying prices
1:00
um I can go up here to San Francisco huh um but yeah and then the great use of the
1:07
interaction and the uh um on selects uh overlay texts that
1:13
looks really really good yep and the next slide I wanted to look at
1:18
um that price versus the number of reviews and then the actual room type here so naturally we can see that
1:24
obviously the lower prices have a higher number of users there's maybe some more people that go there but it's kind of
1:30
interesting to see the as the price increases and we can see like where those different areas are at with
1:35
different room types so yeah fascinating um wow this is a great data set and
1:43
great visual um there's two comments I have um one is that for this visual on the
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depth Axis or sorry the width axis for Price uh you do have the option for log log scale so for data like this it might
1:58
help reveal a bit more of what's going on sort of at the lower end uh
2:04
but I think that's amazing and then on the Second Step um if you want to jump over to that one
2:10
yeah um the one thing I noticed was the
2:15
the dots seemingly above the map a bit I'm not sure if that was intentional but I just wanted to make sure
2:21
um you as well as other people were aware of the button or where that setting is but you'll notice that by default it actually is like hovering
2:28
over just a little bit and if you click on the edit button which is that little pencil icon that will take you into edit
2:35
mode um is that little offset from map um it's right inside of charts uh yeah
2:44
right there so by default that's it's at 0.01 and if you set that to zero then
2:49
the dots will basically be on the the map itself okay and so so anyway it's
2:55
just like it's less about uh critiquing you and more for everyone else's edification
3:01
um in case they've encountered somewhat of the same uh four Maps yeah I didn't notice that and I wasn't sure how to fix
3:06
it so I appreciate that thank you yeah of course and then one last sort of uh and this is my personal uh design take
3:14
is that for the connections themselves here if you select the um connections
3:21
that um whenever you have a lot of density um like this
3:27
um one bar will sometimes obfuscate others and so you can change the opacity of the color here
3:33
um I do something more like 60 or 70 um I mean there's sort of anything's available but the uh it's in the colors
3:41
section um and that opacity will essentially allow you to see through a bit of the
3:49
this the uh the connections and so it just makes it a little easier to sort of
3:54
navigate and see and but that's just a personal design preference since um
4:01
takes um really awesome presentation cool thank you yeah that's great did you
4:08
get the map off our of our help center yep so the the map of California came
4:15
from your uh your U.S states
4:20
Google Drive yep great yeah very nice
4:26
thank you right anyone else like to present
4:33
oh girl all right go ahead how so I um this is uh really quick because uh I
4:39
after last time uh the presentation uh Bill did uh I think that was a really
4:45
good way to learn how to create a present uh visualize uh uh Geographic
4:51
data so I just replicated it in front of my students to give them an example of
4:58
this and uh so I expended a little bit um you know just to for the homework uh
5:05
let me see how do I share my screen I want to share screen uh Google Chrome
5:13
um share sent
5:18
okay um so this is uh uh basically what oh
5:24
can you see this yes okay so so this is uh what bill
5:29
created uh during the last last weeks uh basically 10 000 cities and uh it was
5:37
uh the photograph I think for the color of the map and uh I went a step further
5:45
uh was this to kind of aggregate um the population of cities into each
5:53
for each country so obviously China would have the largest population city population uh so each country would have
6:00
their own uh one dot per country like you know like this so and then I went
6:07
one more step to look at it based on um you know
6:13
um different continents so it's the casino of Asia as the most population Oceana
6:19
New Zealand Australia has the um least population of city in cities
6:26
that's it okay and these are the continents that the 10 000 cities
6:32
um exist on yes so there's ten thousand dots on that graphic
6:38
uh uh yo I I created a snapshot so this
6:43
is population by I aggregated uh okay yeah
6:49
so that was uh yeah my next question is if you did aggregation in the tool or outside and it sounds like you used the
6:56
tool to create a snapshot which is great because we're actually going to cover that a bit today um in the snapshot so that's uh really
7:02
cool that you you did that um it was quite easy to do it just uh you drag a a column up to the on the
7:10
title bar and it just does it for you yeah yeah absolutely um
7:16
yeah I'll I'll show something in just a moment here that is related to that um but before we do that any other
7:23
commentary for anyone else that would like to present yeah I just wanted to say we love it when people take these
7:29
flows that we put out there and extend them and make them uh more comprehensive
7:34
or give a Different Twist to it nice going
7:41
um I'd like to present mine that's okay yeah go ahead Henry okay uh we'll get it
7:47
up this is from a data set that um I'm a
7:52
big fan of it's the exoplanet data from NASA um so to start out with the field like
7:58
all these dots represent a star that we have found uh planets orbiting around
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um you move forward and they all congregate onto the globe and this is all the locations of the observatories
8:09
uh that actually were responsible for finding these exoplanets uh then we move
8:17
on to the next one and this is all the locations of the exoplanets in the sky
8:25
around us so like if you look up at the sky from Earth depending on where you are around the Sun like this is the
8:32
globe around our solar system that we have found exoplanets from and then the
8:38
next step uh it actually has distance data so uh now all of the dots are
8:44
actually arranged via the number of light years they are away
8:50
um from our location so um that's that's what I have so far I
8:55
have a couple other charts that I'm still working on uh this one's pretty good this is all of the uh single
9:02
location stars that we found um or the observatories that have found them uh Kepler which is a Space
9:09
Telescope is way ahead of everybody else still uh so that's and uh so that's that
9:15
it's it's kind of difficult because the Kepler bar is so large I need to find a way to like get it in screen and still
9:22
everybody else and then um and then this one I just started working on the other
9:28
night this is all or this is is the um kind of breakdown of the stars and how
9:35
many planets they have around them so like the larger circle is the ones we've confirmed one planet and then I believe
9:40
it goes all the way up to eight currently we found one start with eight planets around it so uh that is that's
9:46
something I'm going to continue working on I was actually working on it before this class started but wow it's a really
9:51
fun data set and it's always growing too which is super fun yeah yeah where'd you get that data set
9:58
um just search for like NASA exoplanets they have a great page with so much information that's the best part about
10:05
government agencies they just put everything out there so wow
10:12
that is incredible um yeah that was really really awesome uh both from a Content perspective but
10:17
also the visuals the uh the colors at the end I noticed a few red as well there's uh green and red
10:24
does that have any meaning that that did I have already forgotten what it was though okay okay um how did I do that
10:31
that was oh that's the that was the planet numbers I don't know that's the size the oh the colors were the system
10:38
distance that's right um yeah it goes from like 1.3 light years like 8 500 or something like that
10:45
and um if I recall correctly the visual where you had the the dis like the
10:52
exoplanets a set distance away you actually still use the map function to
10:57
set those distances right so I think what's I love this one where it really extends the idea of like what is the the
11:05
um a map here where it's a map of the Earth but now we're taking it and using those distance measurements to share
11:11
something uh as more of like in space as opposed to a dimension of like
11:17
population like household so um I love the different ways Maps can be used here we've seen quite a different quite a few
11:24
here but I love that Visual and I don't know what you're thinking for that last one if you're thinking of like a pyramid
11:29
look um that might be cool yeah but uh right now I think they're overlapping and and the one little button I'll just hint
11:35
towards because you might um encounter it um or it's it's sometimes a little
11:41
tricky to find is within additional Dimensions there's a little field called Direction and it basically says in what
11:48
way does it disperse vertically horizontal or through the depth Dimension okay so I'll just point you to
11:54
that play with that and that might help help on that last step but uh okay yeah
11:59
that was awesome that was awesome guys those are amazing presentations from
12:05
everybody uh just kind of Blown Away uh with the start of this so you guys are
12:10
starting the bar high for me to dive into hierarchies and so um I'm a little nervous but that was
12:16
really cool um and if you guys are open to it I would love to start um sharing these with other with more of
12:23
a larger population so we can talk separately or I'll probably email separately uh Jessica's uh take on that
12:29
but uh to be able to amplify and and showcase some of these I think would be well worth it
Diving into Hierarchies
12:34
um so for today we're diving into hierarchies um and specifically the one we are going
12:41
to dive into together um actually close this one is related to
12:47
creating a balance sheet um and so I point to a balance sheet because it's sort of a very easy way to
12:54
think of a hierarchy relationship um but in a way that you don't typically
Balance Sheet on Hierarchy
12:59
see a balance sheet shown um and so here we have assets and liabilities and shareholders or
13:06
stockholders equity which should always be equal to each other that's why it's a balance sheet that the number of assets
13:11
should equal number of assets Plus or liabilities plus shareholders equity and
13:16
So within each of these this first view you can see sort of the the big picture in some sense the
13:24
um the hey Mike a full span here yes can you go full screen yeah is it um let me I just have you in
13:32
your in your uh box sorry okay yeah let me uh I'll present
13:39
this way because I know the text is a little um yeah thank you small here but um yeah
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and so each of these outer components is uh one of the line items So Good Will
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um sort of the the list goes through and this uh company is actually T-Mobile um if I go more to the side here and uh
13:57
we'll play around with some of the the ways to to visualize this and rotate it but
14:02
um I thought some of the interesting aspects uh to this um one were the the really large values
14:09
here on the asset side was Spectrum licenses so 82 billion dollars worth of spectrum
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licenses so the license for that area of spectrum that they own is by far their
14:20
their largest assets um and where was the other one
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I can't remember the other one was or what the other Insight was um I guess long-term debt but that's not too surprising but anyways um what
14:34
you'll notice here is one there's somewhat of a snakey design here where we're using
14:39
um lines or area charts to connect these data points together the height here is
14:45
equivalent to the dollar amount so it's essentially a bar graph on one angle but
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it's also a hierarchy showing the relationship back to the the center and so we'll show this through a variety
14:58
difference means but you can also show this not just in a circle but also
15:04
vertically here and this might be a little easier to to see and understand
15:09
um and I can actually rotate this as well um oops
15:16
yeah wrote this is 90 degrees and that also sometimes aids with understandability
15:22
um so we'll go through basically the the creation of these um and one thing I'm just going to note is that it's a little
15:27
more technical but I think we'll uh in the process learn quite a lot around how
Fixing a Flow in an Error State
15:33
to actually um and it looks like this might have gone into an error state so
15:39
if your flow ever gets into a state where something doesn't look right I recommend refreshing the page
15:45
or save and refresh and that is typically an artifact of the preview window this is a preview window of the
15:51
presentation um and that then when you go through playback um it's a it runs the script again but
15:58
it's anyways sometimes you can get into a state where the preview window is not accurately reflecting what the
16:04
presentation view will look like so that does happen on occasion so anyways that's the the visual that
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we're going to go through and start to to create and so this can be applied to a balance sheet a cash flow statement an
16:16
income statements a hierarchy of information and even to our points of of being able to show all the different
16:22
areas of flow so still sort of a work in progress and a little large but these
16:27
are something bill and I have been working through these are all the top level areas uh that we are covering the
16:33
flow homepage you guys have gotten very familiar with most of our work here together has been within swarms and
16:40
different components of swarms will probably very quickly go through quite a lot of these other groups for images
16:46
texts and models and sort of things just to check the box but we'll hopefully get
16:52
be able to share this out with you guys and we're marking down what we've gone through already what we have yet to go
16:58
through that way you can sort of see the the whole Gambit of of what is available
Nuances of Labels
17:04
the one thing to note and something I will acknowledge that we are still working through is labels have a lot of
17:10
nuance to them you'll notice that the labels here are radial in in pattern
17:15
where they radiate outwards um aiding in their ability to be deciphered but there are some issues
17:22
like right here that you know is just because of the crowding of information
17:27
um in that x-rap might be on so we'll cover some of the edge cases of what we're working through um but uh but how we think this is going
17:35
to be unlocked is with templates which are coming out soon where we're not
17:41
coming out soon but is something I think you guys will be more heavily involved in where after creating some a flow like
17:48
this like a hierarchy that is more detailed that we can save it as a template that then allows anyone to
17:54
upload data that has a similar format to reuse basically the perspectives and the
18:00
colors and and some of the other characteristics but with the different data sets to help someone get going
18:06
because as you'll find out your original you'll see here there's a few components to building one of these that's
18:12
important for for us to know as as sort of the core designers here um but we'll note that they will get
18:19
easier with templates so with that let me actually start to dive in
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um and so for this first let me reference how you can actually get to this data so once again going to our
18:32
data Library we will be using a training data set for T-Mobile
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so this is within your demo media and assets folder which I'll Place into the
18:44
chat window again um on the chat window
18:50
here we go and
18:59
oh and Mickey I just saw your message sorry um I'm so sorry we skipped over you if we have some time at the end
19:04
let's make sure to have you presents um um yeah let me finish this thought but
19:10
uh we definitely won't don't want to miss your presentation so apologies for that okay so let me go back here
19:18
um yes so I put that into the chat window so this is going to be inside of training data sets
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um and we have T-Mobile financial statements and we have it saved as a Google sheet so that everyone can
19:30
basically look at this data first as well as we're going to use this to import in to look at a few things so
19:37
essentially what we have here is each of these is the line item on a cash flow or on on these reports and that each of
19:44
these can be categorized into a larger category and then a subcategory and then the details for for each as well as we
19:51
have this information both for the year 2020 as well as 2019. we have the dollar
19:58
amount here in millions and then I've actually gone ahead and multiplied it out by a million to show the real value
20:04
here since when we have the auto rounding inside of our our system
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um it's uh it reads this still is 82 000 um as opposed to 82
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um a trillion or billion um so anyways is there any particular way that
20:24
you're organizing that in terms of you know top down
Long Dataset vs. Wide
20:30
yeah so the most important thing is that this is a long data set rather than
20:35
locked and wide and what I mean by that is that you could very much very easily also see this information depicted this
20:43
way where you have 2020 as one column and you have 2019 as a separate column and that's totally fine you could
20:49
actually do it that way just recognize that 2020 will need to be its own swarm
20:54
and 2019 will be its own swarm and if you wanted to combine the two in either
20:59
uh hierarchy or to show something over time that it needs to be in its own
Unpivoting
21:05
column and so that process is called unpivoting and if we get more into the
21:11
data transformation that's a whole whole bag of worms that is a little outside of
21:16
the scope for what we're going to be covering um but definitely is is somewhat necessary here but how you actually get
21:22
this to this data is kind of cool I think is you can actually get this from the SEC website so if you go in to the
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SEC go to filings you can go into Edgar and actually search search for a company
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or fun name so we can type in T-Mobile here
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and once we open that up we can open up the 10K and we'll see the 10 cues make sure to
21:51
click on the 10K and specifically open the filing that was made then then click
21:56
on interactive data I know there's a lot of like clicks here so interactive data
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and then there's a little button that says view Excel documents I think it's kind of hidden with your system but uh
22:09
that's okay because at the end of the day you get a pretty impressive or you get a document that contains
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pretty much everything you need um so here we have the the data and we
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have all of this on different tabs and basically we can use this balance sheets
Column for Category
22:27
uh to take what is current liabilities and what we would do is actually add
22:33
over to it so that we have a column for category
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so this would be assets and then I'll create another call or one
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called subcategory and this is current assets
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and so what you're seeing me do is essentially categorize all of these
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um and I will not include the totals so we would not include the totals here since we don't want that to be part of
23:05
the aggregation but I do the same thing for liabilities
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and I'm just going to skip ahead here um the there's also long-term liability
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it's not just currents but I'm sort of skipping that categorization since we
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already have the data I just wanted you to know where you can get it because you could do this for any balance sheets and
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lots of information so now that we have that downloaded
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um what we'll do is copy over this URL and on inside of flow we are going to
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click on select slash upload the loader type we're going to do Google spreadsheets and paste in this link and
Importing the Data
23:48
when we import we will import that data that data in
23:53
and we will then very quickly click on edit slash re-upload in the future there
23:59
will be a button called Data transformation that will take you basically to the same spot and the thing
Snapshots
24:05
we're going to focus in on is snapshots um because this is where we are adding the categorization or the the creation
24:13
of the hierarchy by creating groups so there's little row groups here and how sort of mentioned it last earlier but
24:20
essentially what you do is you drag and drop up to this little section that says drag here to set row groups and so I
24:28
want to drag them in order so I want to have category on top and then I want subcategory beneath that and So within
24:36
this you'll see that there's been updates already so we can see assets here and if I click the the carrots I
24:42
can see that there's other assets and current assets and I can explore each line item so I've already grouped things
Value Aggregations
24:49
together and then I can perform aggregations so I can take the real value and go to
24:58
Value aggregation sum so now I'm summing up each of these line items so that at
25:04
the next level you're seeing the additional amount and so I'm going to do
25:09
that here for Value as well
25:14
and I'll skip through sort of the other ones um you know one other one we might do
25:21
here maybe just for category no Optical leave it like that actually
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um and the most important thing to do is to click this great snapshot button so I have to set it up you want to make
25:32
sure to take that snapshot of the information and so the now that is saved in that manner
Sorting a Column (Ascend or Descend)
25:39
um the other thing you can do as well as sorts so just by clicking on a column you'll sort it up ascending or
25:45
descending and that's does impact the visualization and the order in which the
25:51
uh columns appear so from here we've created a snapshot
25:56
and so if I close this snapshot is right below data source
26:02
because there can only be one snapshot per swarm you can't you can create multiple snapshots but
26:10
um you can only have one snapshot per swarm so that snapshot carries through to the different steps and I didn't
26:16
cover this in the morning session yesterday and I I realize I should have but I want to just call out sort of how
26:23
this is structured by showing it first in a scatter plot and then we'll jump into uh hiring so the first thing to
Hierarchy level
26:31
know is that there's some automatically created Fields called hierarchy level
26:37
which is basically one two three um based on where it is on this uh in
26:42
this data set where we have three levels the the top level the the sub subcategory and then the actual line
26:49
item um and so um on the Heights I'm just gonna put
26:56
um I guess value sure that'll be fine now the depth axis I will put a hierarchy
27:03
group okay so hopefully this will start to make sense
27:09
um in just a just a moment here uh if you bear with me so basically there's
27:14
three levels of the hierarchy and uh maybe it's just to call out that there's a field called hierarchy level I'm
27:20
actually just going to switch back over to to hierarchy because that's actually how you typically create these all right
27:25
so this is hierarchy um and it by default starts with a circular layout you can switch that to a
27:31
linear layout which I think let's just start with here and then we'll switch to Circular in a moment
27:37
um and so this is level one this little dot here on the always left level two is the middle and level three is this third
27:45
one and that relates to the data um where if I go to snapshot one this is
27:50
level one uh level two and then level three is actually each line item so each each actual line item there so I do not
27:57
need to bring in detail up into the grouping um it's not necessary for to
28:03
add the actual line item um onto the hierarchy okay so from this uh we might want to
Colors
28:11
add some colors um so we could do this in a number of ways one thing we could do is do a color
28:17
scheme um based on let's do this based on category okay this is
28:27
actually a good example of where you might get confused and let me just clear this up a little bit so
28:34
you'll notice that we see the first and the last levels but are missing level
28:39
two and we selected category and if I select subcategory we'll see level two but are missing level one because what
28:46
we're trying to do is apply a color scheme based on the data that is contained there based in based on the
28:52
subcategory here and okay and so
28:58
um if you look at the snapshots you'll notice that um for category there is no category
29:06
listed at this top level for assets or current assets um
29:12
um yeah and and so the way to remedy this is to have these filled in and so
29:17
we can do that by going to Value aggregation first um and a little bit of a uh yeah
29:24
something to a small detail here it's a easy to miss but
29:30
um but yeah is something that's you might encounter and so now essentially we are coloring this based on the first
29:36
one it sees as opposed to being actual representative of what subcategories are
29:42
really there so it is somewhat forcing it's as opposed to being uh truly
29:47
correct so I don't know if that all makes sense to everybody but I sort of want to call it out um as one way to uh to do this
Labels
29:56
okay so to help you understand what's there let's add some labels so on this
30:02
snapshot or on this swarm we're going to click on new labels and the first thing we'll do is click on hierarchy group and
30:09
hierarchy group basically takes all of the hierarchy levels that are not the last node level and adds the name to
30:14
them so this is whatever was grouped on so here we have assets on the bottom we have liabilities and general Equity up
30:20
on top um and if I want to put labels on the Node
30:26
level that I need to create another label object and I can do that by duplicating this or if I go back to the
30:34
Swarm I can also click on new labels again and this will create another labels asset and on this label I want to
30:41
bring in the item which is the very it will only exist at the node level since
30:48
item does not appear at the at the upper levels and so you'll notice that the
30:55
text is all running into each other and a bit difficult to read so what we'll want to do is first turn off wrapping
31:01
this will make it so the text does not wrap to a new line and then in addition
31:08
we might want to reposition this information so we will want it left sent
31:13
left of the dot and be on the center of the dots and
31:22
um this I believe might be an instance where I just need to save and refresh um so let me go ahead and save control s
31:30
and if I refresh um there might be something just going on with the preview window for labels
31:37
which I've mentioned have have a little bit of uh stuff going on so yeah you'll
31:42
see that the the font or the the labels are now resolved
31:48
um and I'll space these out just a little bit by adding some Heights just to call out sort of these little
31:53
components that you can start to Intuit these uh account for the
31:59
um measurements of the size of the this hierarchy um both in width and Heights and this is
32:06
controlling where you're placing the spacing of of this information
Connections
32:12
um so the last thing to do here is to add in some connections so what we're going to do is actually add connections
32:19
based on I'm sorry we're going to click on connections based on hierarchy level
32:24
so it's a little drop down based on hierarchy level and that will create the connections based on those hierarchies
32:30
that we assigned now this is sort of uh I think pretty interesting and uh
32:35
putting more more typical for 2D view um you know there might be more you'd
32:41
want to do for some of these labels some some sort of Tricks here are are to bring it out a little bit so that it
32:48
stands in front and you can also add a background so if it is obfuscated that
32:53
you can make it a little more clear to to read through by adding in backgrounds
33:00
um but the the thing I wanted to really highlight here is I will add another step is that in three dimensions you can
33:07
actually use the height so here what we're going to use for Heights is that aggregated
33:12
um and actually I'll use just regular value in this instance but now you'll
33:17
notice that the dots are offset based on their aggregated real value
33:24
and the thing that we've been sort of uh encouraged people to do is to create an
33:31
area chart from this so if I click on new area charts an area chart is a
33:37
little different than the connections back to the
33:42
axis in that it fills in between data points as well I mean somewhat of like a
33:49
Sankey kind of way where you're seeing the distribution I'm going to alter the
33:54
size of this just a little bit here to make it a little less tall so you can more easily see
34:01
things and the one thing you might also want to do from this is rotate it so if I rotate
34:09
this minus 45 degrees along the width axis makes it just a
34:16
little bit easier to see some of that depth now the reason I'm not going all the way to minus 90 degrees
34:22
is that's at least for looking at it straight on the texts sometimes are
34:28
overlaying each other so we could have a whole lesson just on labels and and formatting and stuff like that and we
34:34
might but I think what we'll mostly find is that by nepotizing these and putting
34:40
them into formats that really we know work that should solve for the majority of cases so that's sort of what we're
34:45
banking on a bit more and I think you guys are going to be more critical to that as well as some ability to interact
34:52
with this we won't uh have you guys do it but we have just briefly show we have a node
34:59
editor which allows you to create a very complex interactions where if I click on a DOT
35:05
here it will cause other things to occur based on whatever I set up in the node editor that's for a totally different
35:12
topic and I'm not going to cover that but just sort of highlighting that that will be a part of hierarchies so you
35:21
know last but not least here just to show how we can transform from one visual to another if I change this from
35:27
linear to Circular you'll see that the the switch is pretty much automatic and
35:32
that's uh yeah I can sort of go from there the one thing I wanted to call out
35:37
for radial text or sorry for um for these types of graphs that are
35:43
circular is that this works fine when you're at an angle here
35:50
um of like you know 90 degrees or something where you can still read everything
35:55
um but that you might especially if you get into more of like a 355 or or a full
36:02
circle that you want the text to radiate outwards and so to accommodate that what
36:09
I'll do here is on um this last line for label two let me
36:14
duplicate this and I'll turn off the first one and on the second one I'm going to click this little radio button
Rotations
36:21
and I will also click enable rotation and it looks better but it still looks bad the reason it looks bad is because
36:27
anytime you use radial these radial buttons that you need to set the
36:34
position center Center Center and then you'll be at the right spot and so now these are more easy to read and still
36:41
face you as you rotate around the object and there's more we could do like I
36:47
mentioned but I will sort of pause there so I know I've covered quite a bit here with hierarchies as well as the root of
36:55
hierarchies which is snapshots and snapshots can be used both for that
37:02
aggregation buts and I realized this after the fact here I actually
37:07
aggregated everything for 2020 and 21. it's uh the reason being is that in that
37:13
snapshot one year 2020 and 2019 are both
37:18
there and so I actually want to filter this I mean neglected to do that and so I can easily do that here if I go into
37:24
here and just type in 2020 or sorry let's click the filters of
37:30
equals 2020. and so now this data set is only just 2020. and
37:38
um I clicked I was doing that to the raw data State set here as opposed to
37:44
snapshot so just a note to be on the right view so to be on Snapshot here and
37:50
then I want to filter this only look at year 2020. so now we'll update that snapshot
37:57
and that should Ripple through to then update all of these visuals and those
38:03
interactions so uh sorry about that but I'm glad you guys get to see sort of
38:08
this in action um so let me pause there to see what questions you have and what I can
38:14
elaborate on
38:24
Michael what other than financial data what else have you found this useful for
38:30
yeah so um we also have seen it use um
38:36
trying to think here we've seen it used in an m a transaction
38:42
whereas basically an org structure like here's one whole business unit as well
38:48
as the geographies so it was basically like Finance you know like where does Finance it or like sorry the like an
38:57
employee layouts um or um uh interactive org chart yeah interactive org chart
39:03
that's yeah a good framing um and that actually reminds me um and this is what I wanted to do quickly with
39:09
um um uh the information that have showed because this is kind of an interesting
Maps and Hierarchies
39:15
use of both Maps plus hierarchies um so if I just create a flow here
39:21
quickly and select from that's 10 000 cities data sets
39:26
um so just from that uh sample data sets 10 000 cities that I can create a
39:32
snapshot here that looks at um let's do
39:37
we'll just do country um for now there's far more that you could do here
39:43
um and actually I'll put consonant too so we'll have uh country and consonants uh update that snapshot and so now if I
39:50
select that snapshots and add a map and actually place these dots on the map
39:58
so if I do this based on coordinates using map one and I'll
40:05
select latitude and longitude that will work
40:10
um but the one thing I neglected to do here and is sort of the the interesting
40:16
way to show this is that we can aggregate this latitude and longitude
40:23
um based on averaging so if I average these I inevitably find sort of the uh
40:28
the the center the geographic center um for the most further SMH cases um for
40:35
each of these and so what you can do is in this snapshot if I change this to a
40:41
color scheme based on hierarchy level um and just for this I'll also add in
40:48
some additional Dimensions height based on those hierarchy levels um and I'm going to invert it so three
40:55
one um so if I do
41:02
0.25 to zero this is the height off the map and I can
41:09
actually go in still to add in connections and add in based on
41:14
hierarchy level and I'll make the transparency of this more like 40. but
Structures aggregating info
41:20
you can start to create these structures now which are aggregating information
41:25
and it's placing at a distance off the map based on something you're aggregating so the better thing to to
41:32
aggregate is something like population or something like that but now you're seeing the middle of each of them so
41:38
this is kind of one of those things where it's a combo of the two it's a both a hierarchy but it's also geospatial and I think that has a lot of
41:45
Promise as well for being able to show aggregations so still a lot more to
41:52
explore I think in aggregations as well as the ability to interact but um we'll be very curious to see if you guys have
41:58
other ideas on what you'd like to see that is sort of um somewhat relationship relational data
42:05
it's a little different than a graph database that's for sure um could you label that Center Point
42:11
that is the source of the hierarchy uh you can great question
42:18
um the um the only way to do that is to really add in a value that is a dummy value
42:27
um so if I go into this snapshot basically I need a something up on top
Type in a Snapshot
42:33
here um and so I know this data set already and that I have something called type
42:40
which is balance sheet for every line and so if I put type balance sheet
42:46
that will actually now be the the top level and so now I'll see sort of a root node
42:52
in the very center now it's not quite accurate because this is adding the two together
42:58
which um doesn't really work but um anyways I just wanted to quickly show
43:04
you where you could do that so you can you could put labels on the countries
43:10
there at the top of those pyramids yes sir right yes yeah so labels here
43:20
definitely um yes
43:28
yeah that's powerful thanks um and so here I'm selecting country is the label but I actually only want to
43:35
label when it's when the column hierarchy level
43:41
is greater than or sorry is less than in this case three
43:50
because I don't want it to show up on the dot level but I do want it to show up here on the the country level
43:57
um and so um the other thing here is this is radial and I want it to basically
44:05
uh be further away
44:13
and that almost worked okay sorry I'm diving a little too deep into some more
44:18
experimental to your stuff but um but yeah I think that's an interesting sort of uh
44:23
use of hierarchies that is a little bit more emerging it's a pretty common use
44:29
case to label the highest level and maybe the second highest level in these
44:34
hierarchies and not label the details just because there's so many of them
44:43
all right what other questions do you guys have
44:50
okay I know it ran a bit over um so I appreciate you guys sticking on here
44:56
um I think the uh that was really awesome this was probably one of my favorite days to see you guys presents
45:02
uh those are really awesome um and yeah if you guys want to create some AR videos with those or anything like that
45:09
um I would be totally game to to do private sessions for you guys to to help record those or whatever
45:14
um I think that's awesome um so really inspiring to see and we're available here to help you homework is
45:21
very similar here um where it's basically you know find some hierarchy data well we can point you to this data sets or even you could
45:27
reuse the 10 000 cities like we just showed um but you know practicing there and you'll probably run into a few more
45:34
things to ask about I'd say um so I appreciate your sort of uh
45:40
uh kindness or understanding um while we we
45:47
still make some hierarchy updates Hey Mickey hey Michael I had one question do you
45:55
think next week we could cover how to potentially animate through data that
46:01
has a Time access yeah great Point let me take a note
46:06
yeah animation is a pretty important aspect um the really short answer is in today's
46:13
platform the way we do that is to create two steps first step and then second step and the first step you just apply
46:19
filters to the date and so it ripples in through that time and there's actually other
46:26
ways to do it too which we we might cover as well um but that's sort of the simplest way
46:31
and that the other thing to just quickly note because I I think is really powerful and use it a lot is
46:38
um in-step details you can control the amount of time it takes to go from one
46:43
step to another um and so um I'll just
46:50
you know just put this into random perhaps and turn off connections so if I
46:57
were to to do this as a movement to have dots then I could quickly change the
47:03
amount of time this takes you know if I make it like 30 seconds it's going to be way more dramatic and slower moving than
47:10
if I were to make it two seconds which is the default so just something to be
47:15
aware of and uh yeah know how you can sort of use that and there are some
47:20
other details within this just so you're aware there's a little animation Tab and there's some some details here for
47:27
ripple duration and item duration um yeah which we might get into uh it's
47:33
yeah might get into you but because uh last week in Bill's presentation he showed how the data dots splashed out to
47:40
the various regions of the map and I was like snagging so uh even if it doesn't happen
47:46
in the class I know it's capable of some really fascinating stuff like that so yeah we can get an idea about how to
47:52
inter interact with the timeline that would be a real uh yeah animation is one of my favorite
47:59
parts of the product actually for for dramatic presentation so that that will be fun to present that
48:07
next week all right uh other questions otherwise
48:12
Nikki I do want to give you the floor if you do want to present no I figured what I learned today about hierarchies would
48:19
help me with some problems I was having so I'm out okay perfectly content to present next time okay okay sounds good
48:25
then we'll do that um cool any other questions or comments
48:31
otherwise we will close up for the day I just have one comment that I end up uh closing out most of these sessions with
48:37
and that is if you are stuck or if you think there must be an easier way or a better way reach out to us with a
48:44
question we've got a lot of it a lot of tips we can that we can provide to you
48:50
so there's no such thing as a silly question in this in this in this space so we're happy to help
48:58
and to the question of getting getting this flow um this will actually a good way to uh
49:06
quickly uh point to one thing um so a few things in the share dialogue
49:11
there's a little button called share and you can create a public link so when
49:17
I click that button for uh creating a shareable link this you link is like a
49:30
of it if they want to use it used for their own or to remix basically you can
49:36
also share it privately where you can put someone's email or if you ever have a question for any of us you might be
49:42
familiar put in Michael at flow or Bill at flow or industry or Json app flow and
49:49
then it will be sent directly to us and then for some Enterprise accounts we have organizations and some other ways
49:56
to to share um but just sharing the ways you can share but the last thing I wanted to
50:02
show was Discovery so this is not used a ton yet but um we're hoping more will is that when
50:09
you click on publish for Discovery there is a tab on the Lister called Discovery
50:14
so if anyone wants to publish there you can't so you can take any of the flows
50:20
that you have created and publish for Discovery and then we can see them too
50:26
and uh we'll occasionally bring over some into the featured tab but that
50:31
mostly is Monitor or managed by us and the Discover tab is sort of open to everybody so you'll notice there is one
50:38
there called bound sheet from training and that is today so you can use that as sort of a a reference points or
50:46
um for learning on your own okay
50:52
great all right well thank you guys so much for your attention and amazing
50:57
presentations uh really exciting to see the progress and look forward to next week thanks everybody
51:03
bye-bye everybody thank you thank you thank you thank you bye thank you